Overview

Dataset statistics

Number of variables34
Number of observations100000
Missing cells1230479
Missing cells (%)36.2%
Total size in memory25.9 MiB
Average record size in memory272.0 B

Variable types

Text27
Numeric7

Alerts

homedescription has 47652 (47.7%) missing valuesMissing
neutraldescription has 97579 (97.6%) missing valuesMissing
visitordescription has 49343 (49.3%) missing valuesMissing
score has 73823 (73.8%) missing valuesMissing
scoremargin has 73823 (73.8%) missing valuesMissing
player1_name has 8921 (8.9%) missing valuesMissing
player1_team_id has 8976 (9.0%) missing valuesMissing
player1_team_city has 8976 (9.0%) missing valuesMissing
player1_team_nickname has 8976 (9.0%) missing valuesMissing
player1_team_abbreviation has 8976 (9.0%) missing valuesMissing
player2_name has 71359 (71.4%) missing valuesMissing
player2_team_id has 71174 (71.2%) missing valuesMissing
player2_team_city has 71174 (71.2%) missing valuesMissing
player2_team_nickname has 71174 (71.2%) missing valuesMissing
player2_team_abbreviation has 71174 (71.2%) missing valuesMissing
player3_name has 97504 (97.5%) missing valuesMissing
player3_team_id has 97462 (97.5%) missing valuesMissing
player3_team_city has 97462 (97.5%) missing valuesMissing
player3_team_nickname has 97462 (97.5%) missing valuesMissing
player3_team_abbreviation has 97462 (97.5%) missing valuesMissing
eventmsgactiontype has 32337 (32.3%) zerosZeros
person1type has 2028 (2.0%) zerosZeros
person2type has 71170 (71.2%) zerosZeros
person3type has 86194 (86.2%) zerosZeros

Reproduction

Analysis started2023-07-13 14:06:03.109352
Analysis finished2023-07-13 14:06:05.116196
Duration2.01 seconds
Software versionydata-profiling vv4.3.1
Download configurationconfig.json

Variables

Distinct28819
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:05.420008image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1000000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3584 ?
Unique (%)3.6%

Sample

1st row0020100714
2nd row0029600273
3rd row0040200145
4th row0020700175
5th row0020900639
ValueCountFrequency (%)
0040300141 13
 
< 0.1%
0031000001 13
 
< 0.1%
0021900023 12
 
< 0.1%
0020400006 12
 
< 0.1%
0021100264 11
 
< 0.1%
0020100329 11
 
< 0.1%
0021300720 11
 
< 0.1%
0041100302 11
 
< 0.1%
0020500281 11
 
< 0.1%
0022200981 11
 
< 0.1%
Other values (28809) 99884
99.9%
2023-07-13T22:06:05.810998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 472810
47.3%
2 144401
 
14.4%
1 103200
 
10.3%
9 49608
 
5.0%
4 42553
 
4.3%
6 39528
 
4.0%
7 38689
 
3.9%
3 37526
 
3.8%
8 36129
 
3.6%
5 35556
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 472810
47.3%
2 144401
 
14.4%
1 103200
 
10.3%
9 49608
 
5.0%
4 42553
 
4.3%
6 39528
 
4.0%
7 38689
 
3.9%
3 37526
 
3.8%
8 36129
 
3.6%
5 35556
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1000000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 472810
47.3%
2 144401
 
14.4%
1 103200
 
10.3%
9 49608
 
5.0%
4 42553
 
4.3%
6 39528
 
4.0%
7 38689
 
3.9%
3 37526
 
3.8%
8 36129
 
3.6%
5 35556
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 472810
47.3%
2 144401
 
14.4%
1 103200
 
10.3%
9 49608
 
5.0%
4 42553
 
4.3%
6 39528
 
4.0%
7 38689
 
3.9%
3 37526
 
3.8%
8 36129
 
3.6%
5 35556
 
3.6%

eventnum
Real number (ℝ)

Distinct798
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean272.30645
Minimum0
Maximum985
Zeros146
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:06.259409image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile26
Q1132
median265
Q3399
95-th percentile555
Maximum985
Range985
Interquartile range (IQR)267

Descriptive statistics

Standard deviation166.6062107
Coefficient of variation (CV)0.6118335084
Kurtosis-0.7337492935
Mean272.30645
Median Absolute Deviation (MAD)134
Skewness0.2788708008
Sum27230645
Variance27757.62943
MonotonicityNot monotonic
2023-07-13T22:06:06.319911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 232
 
0.2%
154 225
 
0.2%
163 225
 
0.2%
251 222
 
0.2%
266 220
 
0.2%
353 220
 
0.2%
95 219
 
0.2%
361 219
 
0.2%
40 219
 
0.2%
29 218
 
0.2%
Other values (788) 97781
97.8%
ValueCountFrequency (%)
0 146
0.1%
1 167
0.2%
2 192
0.2%
3 168
0.2%
4 232
0.2%
ValueCountFrequency (%)
985 1
< 0.1%
956 1
< 0.1%
888 1
< 0.1%
876 1
< 0.1%
856 1
< 0.1%

eventmsgtype
Real number (ℝ)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.97472
Minimum1
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:06.369852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile9
Maximum18
Range17
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.626988758
Coefficient of variation (CV)0.6609242305
Kurtosis2.207642504
Mean3.97472
Median Absolute Deviation (MAD)2
Skewness1.254027721
Sum397472
Variance6.901069932
MonotonicityNot monotonic
2023-07-13T22:06:06.413568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
4 22327
22.3%
2 20089
20.1%
1 16478
16.5%
3 10476
10.5%
6 9748
9.7%
8 8884
 
8.9%
5 6378
 
6.4%
9 2781
 
2.8%
12 913
 
0.9%
13 911
 
0.9%
Other values (4) 1015
 
1.0%
ValueCountFrequency (%)
1 16478
16.5%
2 20089
20.1%
3 10476
10.5%
4 22327
22.3%
5 6378
 
6.4%
ValueCountFrequency (%)
18 219
 
0.2%
13 911
0.9%
12 913
0.9%
11 22
 
< 0.1%
10 400
0.4%

eventmsgactiontype
Real number (ℝ)

ZEROS 

Distinct98
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.26125
Minimum0
Maximum109
Zeros32337
Zeros (%)32.3%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:06.472800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile71
Maximum109
Range109
Interquartile range (IQR)5

Descriptive statistics

Standard deviation20.81184158
Coefficient of variation (CV)2.247195743
Kurtosis7.755216191
Mean9.26125
Median Absolute Deviation (MAD)1
Skewness2.909805892
Sum926125
Variance433.1327498
MonotonicityNot monotonic
2023-07-13T22:06:06.534330image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32337
32.3%
1 28430
28.4%
2 6424
 
6.4%
5 5014
 
5.0%
11 4961
 
5.0%
12 4381
 
4.4%
4 1902
 
1.9%
79 1495
 
1.5%
3 1352
 
1.4%
42 1201
 
1.2%
Other values (88) 12503
 
12.5%
ValueCountFrequency (%)
0 32337
32.3%
1 28430
28.4%
2 6424
 
6.4%
3 1352
 
1.4%
4 1902
 
1.9%
ValueCountFrequency (%)
109 3
 
< 0.1%
108 173
0.2%
107 27
 
< 0.1%
106 7
 
< 0.1%
105 16
 
< 0.1%

period
Real number (ℝ)

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.54748
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:06.584908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.138849691
Coefficient of variation (CV)0.4470495122
Kurtosis-1.186920147
Mean2.54748
Median Absolute Deviation (MAD)1
Skewness0.04629131942
Sum254748
Variance1.296978619
MonotonicityNot monotonic
2023-07-13T22:06:06.627023image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 25798
25.8%
2 25723
25.7%
3 24010
24.0%
1 23602
23.6%
5 750
 
0.8%
6 96
 
0.1%
7 16
 
< 0.1%
8 5
 
< 0.1%
ValueCountFrequency (%)
1 23602
23.6%
2 25723
25.7%
3 24010
24.0%
4 25798
25.8%
5 750
 
0.8%
ValueCountFrequency (%)
8 5
 
< 0.1%
7 16
 
< 0.1%
6 96
 
0.1%
5 750
 
0.8%
4 25798
25.8%
Distinct1782
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:06.885004image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length7
Mean length7.36539
Min length0

Characters and Unicode

Total characters736539
Distinct characters16
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique300 ?
Unique (%)0.3%

Sample

1st row10:51 PM
2nd row12:33 PM
3rd row7:45 PM
4th row10:30 PM
5th row9:38 PM
ValueCountFrequency (%)
pm 93420
46.7%
am 6562
 
3.3%
8:58 418
 
0.2%
9:02 418
 
0.2%
9:00 416
 
0.2%
9:05 403
 
0.2%
8:56 402
 
0.2%
8:57 401
 
0.2%
8:25 394
 
0.2%
9:03 394
 
0.2%
Other values (1121) 96756
48.4%
2023-07-13T22:06:07.211934image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 99994
13.6%
99990
13.6%
M 99982
13.6%
P 93420
12.7%
1 77704
10.5%
2 39687
 
5.4%
0 39391
 
5.3%
3 30694
 
4.2%
9 30141
 
4.1%
4 29633
 
4.0%
Other values (6) 95903
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 336547
45.7%
Uppercase Letter 199972
27.2%
Other Punctuation 99994
 
13.6%
Space Separator 99990
 
13.6%
Dash Punctuation 36
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 77704
23.1%
2 39687
11.8%
0 39391
11.7%
3 30694
 
9.1%
9 30141
 
9.0%
4 29633
 
8.8%
5 29057
 
8.6%
8 28428
 
8.4%
7 19803
 
5.9%
6 12009
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
M 99982
50.0%
P 93420
46.7%
A 6570
 
3.3%
Other Punctuation
ValueCountFrequency (%)
: 99994
100.0%
Space Separator
ValueCountFrequency (%)
99990
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 536567
72.8%
Latin 199972
 
27.2%

Most frequent character per script

Common
ValueCountFrequency (%)
: 99994
18.6%
99990
18.6%
1 77704
14.5%
2 39687
 
7.4%
0 39391
 
7.3%
3 30694
 
5.7%
9 30141
 
5.6%
4 29633
 
5.5%
5 29057
 
5.4%
8 28428
 
5.3%
Other values (3) 31848
 
5.9%
Latin
ValueCountFrequency (%)
M 99982
50.0%
P 93420
46.7%
A 6570
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 736539
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 99994
13.6%
99990
13.6%
M 99982
13.6%
P 93420
12.7%
1 77704
10.5%
2 39687
 
5.4%
0 39391
 
5.3%
3 30694
 
4.2%
9 30141
 
4.1%
4 29633
 
4.0%
Other values (6) 95903
13.0%
Distinct720
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:07.523208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length5
Median length4
Mean length4.13903
Min length4

Characters and Unicode

Total characters413903
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5:42
2nd row0:00
3rd row0:00
4th row0:08
5th row12:00
ValueCountFrequency (%)
0:00 2119
 
2.1%
12:00 1130
 
1.1%
0:01 435
 
0.4%
0:02 359
 
0.4%
0:04 292
 
0.3%
0:03 266
 
0.3%
0:05 221
 
0.2%
0:32 207
 
0.2%
0:31 203
 
0.2%
0:33 197
 
0.2%
Other values (710) 94571
94.6%
2023-07-13T22:06:07.882010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
: 100000
24.2%
1 53914
13.0%
0 52667
12.7%
2 35804
 
8.7%
3 34323
 
8.3%
4 34116
 
8.2%
5 33565
 
8.1%
6 17665
 
4.3%
7 17470
 
4.2%
8 17336
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 313903
75.8%
Other Punctuation 100000
 
24.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 53914
17.2%
0 52667
16.8%
2 35804
11.4%
3 34323
10.9%
4 34116
10.9%
5 33565
10.7%
6 17665
 
5.6%
7 17470
 
5.6%
8 17336
 
5.5%
9 17043
 
5.4%
Other Punctuation
ValueCountFrequency (%)
: 100000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 413903
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
: 100000
24.2%
1 53914
13.0%
0 52667
12.7%
2 35804
 
8.7%
3 34323
 
8.3%
4 34116
 
8.2%
5 33565
 
8.1%
6 17665
 
4.3%
7 17470
 
4.2%
8 17336
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 413903
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
: 100000
24.2%
1 53914
13.0%
0 52667
12.7%
2 35804
 
8.7%
3 34323
 
8.3%
4 34116
 
8.2%
5 33565
 
8.1%
6 17665
 
4.3%
7 17470
 
4.2%
8 17336
 
4.2%

homedescription
Text

MISSING 

Distinct41383
Distinct (%)79.1%
Missing47652
Missing (%)47.7%
Memory size781.4 KiB
2023-07-13T22:06:08.209152image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length71
Median length62
Mean length29.80138687
Min length0

Characters and Unicode

Total characters1560043
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36000 ?
Unique (%)68.8%

Sample

1st rowGRIZZLIES Timeout: Regular (Full 3 Short 0)
2nd rowMISS T. Johnson 11' Driving Floating Jump Shot
3rd rowWashington 2' Layup (2 PTS) (Rozier 1 AST)
4th rowSUB: Smith FOR Blaylock
5th rowSUB: Green FOR Scalabrine
ValueCountFrequency (%)
shot 13174
 
4.7%
pts 12461
 
4.5%
jump 12141
 
4.3%
2 11586
 
4.1%
rebound 11415
 
4.1%
miss 11315
 
4.0%
1 9008
 
3.2%
of 5538
 
2.0%
throw 5352
 
1.9%
free 5352
 
1.9%
Other values (1959) 182217
65.2%
2023-07-13T22:06:08.600844image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
229784
 
14.7%
S 72987
 
4.7%
o 69534
 
4.5%
e 65247
 
4.2%
r 55037
 
3.5%
T 47422
 
3.0%
a 46430
 
3.0%
n 43266
 
2.8%
u 41340
 
2.6%
) 40697
 
2.6%
Other values (60) 848299
54.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 646642
41.5%
Uppercase Letter 441644
28.3%
Space Separator 229784
 
14.7%
Decimal Number 102658
 
6.6%
Other Punctuation 57167
 
3.7%
Close Punctuation 40697
 
2.6%
Open Punctuation 40697
 
2.6%
Dash Punctuation 754
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 69534
 
10.8%
e 65247
 
10.1%
r 55037
 
8.5%
a 46430
 
7.2%
n 43266
 
6.7%
u 41340
 
6.4%
f 37102
 
5.7%
l 35951
 
5.6%
i 34343
 
5.3%
t 33590
 
5.2%
Other values (16) 184802
28.6%
Uppercase Letter
ValueCountFrequency (%)
S 72987
16.5%
T 47422
 
10.7%
P 34268
 
7.8%
O 32380
 
7.3%
B 27151
 
6.1%
D 26393
 
6.0%
R 23714
 
5.4%
F 19888
 
4.5%
U 19220
 
4.4%
L 19189
 
4.3%
Other values (15) 119032
27.0%
Decimal Number
ValueCountFrequency (%)
1 30166
29.4%
2 25764
25.1%
3 13366
13.0%
0 7521
 
7.3%
4 7096
 
6.9%
5 5459
 
5.3%
6 4724
 
4.6%
7 3453
 
3.4%
8 2815
 
2.7%
9 2294
 
2.2%
Other Punctuation
ValueCountFrequency (%)
: 25700
45.0%
. 16104
28.2%
' 15217
26.6%
# 142
 
0.2%
, 4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
229784
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40697
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40697
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 754
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1088286
69.8%
Common 471757
30.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 72987
 
6.7%
o 69534
 
6.4%
e 65247
 
6.0%
r 55037
 
5.1%
T 47422
 
4.4%
a 46430
 
4.3%
n 43266
 
4.0%
u 41340
 
3.8%
f 37102
 
3.4%
l 35951
 
3.3%
Other values (41) 573970
52.7%
Common
ValueCountFrequency (%)
229784
48.7%
) 40697
 
8.6%
( 40697
 
8.6%
1 30166
 
6.4%
2 25764
 
5.5%
: 25700
 
5.4%
. 16104
 
3.4%
' 15217
 
3.2%
3 13366
 
2.8%
0 7521
 
1.6%
Other values (9) 26741
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1560043
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
229784
 
14.7%
S 72987
 
4.7%
o 69534
 
4.5%
e 65247
 
4.2%
r 55037
 
3.5%
T 47422
 
3.0%
a 46430
 
3.0%
n 43266
 
2.8%
u 41340
 
2.6%
) 40697
 
2.6%
Other values (60) 848299
54.4%

neutraldescription
Text

MISSING 

Distinct1398
Distinct (%)57.7%
Missing97579
Missing (%)97.6%
Memory size781.4 KiB
2023-07-13T22:06:08.933508image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length69
Median length66
Mean length30.03015283
Min length4

Characters and Unicode

Total characters72703
Distinct characters65
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1037 ?
Unique (%)42.8%

Sample

1st rowDon Nelson Foul:T.FOUL
2nd rowEnd of 1st Period (7:45 PM EST)
3rd rowStart of 4th Period (9:38 PM EST)
4th rowEnd of 2nd Period (4:40 PM EST)
5th rowStart of 1st Period (11:08 PM EST)
ValueCountFrequency (%)
est 1951
13.3%
period 1923
13.1%
of 1833
12.5%
pm 1798
12.2%
start 913
 
6.2%
end 911
 
6.2%
1st 485
 
3.3%
4th 454
 
3.1%
2nd 450
 
3.1%
3rd 435
 
3.0%
Other values (717) 3544
24.1%
2023-07-13T22:06:09.332142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12287
16.9%
o 4277
 
5.9%
d 3801
 
5.2%
P 3759
 
5.2%
r 3528
 
4.9%
t 3521
 
4.8%
S 2958
 
4.1%
i 2923
 
4.0%
E 2869
 
3.9%
e 2574
 
3.5%
Other values (55) 30206
41.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30325
41.7%
Uppercase Letter 15158
20.8%
Space Separator 12287
16.9%
Decimal Number 8547
 
11.8%
Other Punctuation 2382
 
3.3%
Open Punctuation 1988
 
2.7%
Close Punctuation 1988
 
2.7%
Dash Punctuation 28
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4277
14.1%
d 3801
12.5%
r 3528
11.6%
t 3521
11.6%
i 2923
9.6%
e 2574
8.5%
f 2376
7.8%
n 1875
6.2%
a 1592
 
5.2%
s 699
 
2.3%
Other values (16) 3159
10.4%
Uppercase Letter
ValueCountFrequency (%)
P 3759
24.8%
S 2958
19.5%
E 2869
18.9%
T 2343
15.5%
M 1969
13.0%
O 356
 
2.3%
R 258
 
1.7%
A 164
 
1.1%
I 128
 
0.8%
F 116
 
0.8%
Other values (12) 238
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 2145
25.1%
2 1170
13.7%
3 1134
13.3%
4 1064
12.4%
0 753
 
8.8%
9 596
 
7.0%
8 571
 
6.7%
5 485
 
5.7%
7 369
 
4.3%
6 260
 
3.0%
Other Punctuation
ValueCountFrequency (%)
: 2302
96.6%
. 54
 
2.3%
, 26
 
1.1%
Space Separator
ValueCountFrequency (%)
12287
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1988
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1988
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 45483
62.6%
Common 27220
37.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 4277
 
9.4%
d 3801
 
8.4%
P 3759
 
8.3%
r 3528
 
7.8%
t 3521
 
7.7%
S 2958
 
6.5%
i 2923
 
6.4%
E 2869
 
6.3%
e 2574
 
5.7%
f 2376
 
5.2%
Other values (38) 12897
28.4%
Common
ValueCountFrequency (%)
12287
45.1%
: 2302
 
8.5%
1 2145
 
7.9%
( 1988
 
7.3%
) 1988
 
7.3%
2 1170
 
4.3%
3 1134
 
4.2%
4 1064
 
3.9%
0 753
 
2.8%
9 596
 
2.2%
Other values (7) 1793
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72703
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12287
16.9%
o 4277
 
5.9%
d 3801
 
5.2%
P 3759
 
5.2%
r 3528
 
4.9%
t 3521
 
4.8%
S 2958
 
4.1%
i 2923
 
4.0%
E 2869
 
3.9%
e 2574
 
3.5%
Other values (55) 30206
41.5%

visitordescription
Text

MISSING 

Distinct40370
Distinct (%)79.7%
Missing49343
Missing (%)49.3%
Memory size781.4 KiB
2023-07-13T22:06:09.605425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length76
Median length63
Mean length29.61624257
Min length4

Characters and Unicode

Total characters1500270
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35357 ?
Unique (%)69.8%

Sample

1st rowMISS Perkins 27' 3PT Jump Shot
2nd rowHarris P.FOUL (P4.PN)
3rd rowHornets Timeout: Regular (Reg.3 Short 0)
4th rowSUB: Belinelli FOR Poeltl
5th rowTrent 2' Layup (2 PTS) (Hoiberg 2 AST)
ValueCountFrequency (%)
shot 13292
 
5.0%
pts 11975
 
4.5%
jump 11917
 
4.5%
miss 11291
 
4.2%
2 10947
 
4.1%
rebound 10912
 
4.1%
1 8181
 
3.1%
of 5323
 
2.0%
throw 5124
 
1.9%
free 5124
 
1.9%
Other values (1984) 173623
64.9%
2023-07-13T22:06:09.953999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219309
 
14.6%
S 68698
 
4.6%
o 67848
 
4.5%
e 66058
 
4.4%
r 55619
 
3.7%
a 45437
 
3.0%
T 44961
 
3.0%
n 42237
 
2.8%
u 40083
 
2.7%
) 39132
 
2.6%
Other values (61) 810888
54.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 637732
42.5%
Uppercase Letter 407590
27.2%
Space Separator 219309
 
14.6%
Decimal Number 100059
 
6.7%
Other Punctuation 56651
 
3.8%
Close Punctuation 39132
 
2.6%
Open Punctuation 39132
 
2.6%
Dash Punctuation 665
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 68698
16.9%
T 44961
11.0%
P 33418
 
8.2%
O 30062
 
7.4%
B 25211
 
6.2%
D 24605
 
6.0%
R 22151
 
5.4%
F 18099
 
4.4%
U 17819
 
4.4%
M 17447
 
4.3%
Other values (16) 105119
25.8%
Lowercase Letter
ValueCountFrequency (%)
o 67848
 
10.6%
e 66058
 
10.4%
r 55619
 
8.7%
a 45437
 
7.1%
n 42237
 
6.6%
u 40083
 
6.3%
f 35003
 
5.5%
i 33599
 
5.3%
t 33454
 
5.2%
l 32270
 
5.1%
Other values (16) 186124
29.2%
Decimal Number
ValueCountFrequency (%)
1 29204
29.2%
2 25138
25.1%
3 13122
13.1%
0 7335
 
7.3%
4 6796
 
6.8%
5 5301
 
5.3%
6 4676
 
4.7%
7 3403
 
3.4%
8 2787
 
2.8%
9 2297
 
2.3%
Other Punctuation
ValueCountFrequency (%)
: 24005
42.4%
. 17219
30.4%
' 15267
26.9%
# 156
 
0.3%
, 4
 
< 0.1%
Space Separator
ValueCountFrequency (%)
219309
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39132
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 665
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1045322
69.7%
Common 454948
30.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 68698
 
6.6%
o 67848
 
6.5%
e 66058
 
6.3%
r 55619
 
5.3%
a 45437
 
4.3%
T 44961
 
4.3%
n 42237
 
4.0%
u 40083
 
3.8%
f 35003
 
3.3%
i 33599
 
3.2%
Other values (42) 545779
52.2%
Common
ValueCountFrequency (%)
219309
48.2%
) 39132
 
8.6%
( 39132
 
8.6%
1 29204
 
6.4%
2 25138
 
5.5%
: 24005
 
5.3%
. 17219
 
3.8%
' 15267
 
3.4%
3 13122
 
2.9%
0 7335
 
1.6%
Other values (9) 26085
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1500270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219309
 
14.6%
S 68698
 
4.6%
o 67848
 
4.5%
e 66058
 
4.4%
r 55619
 
3.7%
a 45437
 
3.0%
T 44961
 
3.0%
n 42237
 
2.8%
u 40083
 
2.7%
) 39132
 
2.6%
Other values (61) 810888
54.0%

score
Text

MISSING 

Distinct5324
Distinct (%)20.3%
Missing73823
Missing (%)73.8%
Memory size781.4 KiB
2023-07-13T22:06:10.156821image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.97616228
Min length5

Characters and Unicode

Total characters182615
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1393 ?
Unique (%)5.3%

Sample

1st row14 - 27
2nd row74 - 69
3rd row84 - 103
4th row2 - 4
5th row90 - 75
ValueCountFrequency (%)
26177
33.3%
2 737
 
0.9%
26 600
 
0.8%
6 597
 
0.8%
53 596
 
0.8%
23 573
 
0.7%
4 566
 
0.7%
35 564
 
0.7%
49 561
 
0.7%
29 559
 
0.7%
Other values (150) 47001
59.9%
2023-07-13T22:06:10.414924image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52354
28.7%
- 26177
14.3%
1 14428
 
7.9%
2 11314
 
6.2%
6 10667
 
5.8%
4 10609
 
5.8%
3 10430
 
5.7%
5 10404
 
5.7%
7 10202
 
5.6%
8 9816
 
5.4%
Other values (2) 16214
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104084
57.0%
Space Separator 52354
28.7%
Dash Punctuation 26177
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14428
13.9%
2 11314
10.9%
6 10667
10.2%
4 10609
10.2%
3 10430
10.0%
5 10404
10.0%
7 10202
9.8%
8 9816
9.4%
9 8728
8.4%
0 7486
7.2%
Space Separator
ValueCountFrequency (%)
52354
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26177
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 182615
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
52354
28.7%
- 26177
14.3%
1 14428
 
7.9%
2 11314
 
6.2%
6 10667
 
5.8%
4 10609
 
5.8%
3 10430
 
5.7%
5 10404
 
5.7%
7 10202
 
5.6%
8 9816
 
5.4%
Other values (2) 16214
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 182615
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52354
28.7%
- 26177
14.3%
1 14428
 
7.9%
2 11314
 
6.2%
6 10667
 
5.8%
4 10609
 
5.8%
3 10430
 
5.7%
5 10404
 
5.7%
7 10202
 
5.6%
8 9816
 
5.4%
Other values (2) 16214
 
8.9%

scoremargin
Text

MISSING 

Distinct103
Distinct (%)0.4%
Missing73823
Missing (%)73.8%
Memory size781.4 KiB
2023-07-13T22:06:10.531946image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.831225885
Min length1

Characters and Unicode

Total characters47936
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.1%

Sample

1st row13
2nd row-5
3rd row19
4th row2
5th row-15
ValueCountFrequency (%)
2 2539
 
9.7%
1 2296
 
8.8%
3 2126
 
8.1%
4 1973
 
7.5%
5 1818
 
6.9%
6 1713
 
6.5%
7 1506
 
5.8%
8 1363
 
5.2%
tie 1228
 
4.7%
9 1197
 
4.6%
Other values (47) 8418
32.2%
2023-07-13T22:06:10.699308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 10885
22.7%
1 10079
21.0%
2 5240
10.9%
3 3398
 
7.1%
4 2793
 
5.8%
5 2533
 
5.3%
6 2366
 
4.9%
7 2055
 
4.3%
8 1870
 
3.9%
9 1624
 
3.4%
Other values (4) 5093
10.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33367
69.6%
Dash Punctuation 10885
 
22.7%
Uppercase Letter 3684
 
7.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10079
30.2%
2 5240
15.7%
3 3398
 
10.2%
4 2793
 
8.4%
5 2533
 
7.6%
6 2366
 
7.1%
7 2055
 
6.2%
8 1870
 
5.6%
9 1624
 
4.9%
0 1409
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
T 1228
33.3%
I 1228
33.3%
E 1228
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 10885
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44252
92.3%
Latin 3684
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
- 10885
24.6%
1 10079
22.8%
2 5240
11.8%
3 3398
 
7.7%
4 2793
 
6.3%
5 2533
 
5.7%
6 2366
 
5.3%
7 2055
 
4.6%
8 1870
 
4.2%
9 1624
 
3.7%
Latin
ValueCountFrequency (%)
T 1228
33.3%
I 1228
33.3%
E 1228
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47936
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 10885
22.7%
1 10079
21.0%
2 5240
10.9%
3 3398
 
7.1%
4 2793
 
5.8%
5 2533
 
5.3%
6 2366
 
4.9%
7 2055
 
4.3%
8 1870
 
3.9%
9 1624
 
3.4%
Other values (4) 5093
10.6%

person1type
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)< 0.1%
Missing27
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean4.260420313
Minimum0
Maximum7
Zeros2028
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:10.755531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q14
median4
Q35
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9471962743
Coefficient of variation (CV)0.2223246076
Kurtosis7.065893439
Mean4.260420313
Median Absolute Deviation (MAD)1
Skewness-2.276404651
Sum425927
Variance0.897180782
MonotonicityNot monotonic
2023-07-13T22:06:10.797502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
4 46270
46.3%
5 44754
44.8%
3 3341
 
3.3%
2 3240
 
3.2%
0 2028
 
2.0%
1 298
 
0.3%
7 24
 
< 0.1%
6 18
 
< 0.1%
(Missing) 27
 
< 0.1%
ValueCountFrequency (%)
0 2028
 
2.0%
1 298
 
0.3%
2 3240
 
3.2%
3 3341
 
3.3%
4 46270
46.3%
ValueCountFrequency (%)
7 24
 
< 0.1%
6 18
 
< 0.1%
5 44754
44.8%
4 46270
46.3%
3 3341
 
3.3%
Distinct2371
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:11.091107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.11112
Min length1

Characters and Unicode

Total characters511112
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique395 ?
Unique (%)0.4%

Sample

1st row1483
2nd row64
3rd row0
4th row2734
5th row0
ValueCountFrequency (%)
0 2166
 
2.2%
2544 481
 
0.5%
1495 414
 
0.4%
1717 392
 
0.4%
977 392
 
0.4%
708 376
 
0.4%
2546 359
 
0.4%
201566 335
 
0.3%
2730 333
 
0.3%
201142 305
 
0.3%
Other values (2361) 94447
94.4%
2023-07-13T22:06:11.450443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 91399
17.9%
2 91236
17.9%
0 70364
13.8%
6 53703
10.5%
7 41522
8.1%
3 37551
7.3%
9 34894
 
6.8%
5 32027
 
6.3%
4 31539
 
6.2%
8 26877
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 511112
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 91399
17.9%
2 91236
17.9%
0 70364
13.8%
6 53703
10.5%
7 41522
8.1%
3 37551
7.3%
9 34894
 
6.8%
5 32027
 
6.3%
4 31539
 
6.2%
8 26877
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
Common 511112
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 91399
17.9%
2 91236
17.9%
0 70364
13.8%
6 53703
10.5%
7 41522
8.1%
3 37551
7.3%
9 34894
 
6.8%
5 32027
 
6.3%
4 31539
 
6.2%
8 26877
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 511112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 91399
17.9%
2 91236
17.9%
0 70364
13.8%
6 53703
10.5%
7 41522
8.1%
3 37551
7.3%
9 34894
 
6.8%
5 32027
 
6.3%
4 31539
 
6.2%
8 26877
 
5.3%

player1_name
Text

MISSING 

Distinct2186
Distinct (%)2.4%
Missing8921
Missing (%)8.9%
Memory size781.4 KiB
2023-07-13T22:06:11.702736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length23
Mean length12.83282645
Min length4

Characters and Unicode

Total characters1168801
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique271 ?
Unique (%)0.3%

Sample

1st rowSam Perkins
2nd rowDevin Harris
3rd rowTyler Johnson
4th rowJakob Poeltl
5th rowGary Trent
ValueCountFrequency (%)
chris 1660
 
0.9%
williams 1630
 
0.9%
kevin 1336
 
0.7%
james 1316
 
0.7%
anthony 1255
 
0.7%
johnson 1134
 
0.6%
jason 1063
 
0.6%
davis 1033
 
0.6%
paul 1015
 
0.6%
michael 1009
 
0.5%
Other values (2464) 171468
93.2%
2023-07-13T22:06:12.015408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 98914
 
8.5%
a 95597
 
8.2%
92840
 
7.9%
n 85538
 
7.3%
r 83604
 
7.2%
o 77038
 
6.6%
i 67377
 
5.8%
l 57837
 
4.9%
s 49634
 
4.2%
t 34423
 
2.9%
Other values (46) 425999
36.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 877820
75.1%
Uppercase Letter 192593
 
16.5%
Space Separator 92840
 
7.9%
Other Punctuation 4419
 
0.4%
Dash Punctuation 1129
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 98914
11.3%
a 95597
10.9%
n 85538
9.7%
r 83604
9.5%
o 77038
 
8.8%
i 67377
 
7.7%
l 57837
 
6.6%
s 49634
 
5.7%
t 34423
 
3.9%
d 28409
 
3.2%
Other values (16) 199449
22.7%
Uppercase Letter
ValueCountFrequency (%)
J 19265
 
10.0%
M 17345
 
9.0%
D 15033
 
7.8%
B 14101
 
7.3%
A 12322
 
6.4%
C 12168
 
6.3%
S 11256
 
5.8%
R 10781
 
5.6%
T 9549
 
5.0%
G 8901
 
4.6%
Other values (16) 61872
32.1%
Other Punctuation
ValueCountFrequency (%)
. 3140
71.1%
' 1279
28.9%
Space Separator
ValueCountFrequency (%)
92840
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1070413
91.6%
Common 98388
 
8.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 98914
 
9.2%
a 95597
 
8.9%
n 85538
 
8.0%
r 83604
 
7.8%
o 77038
 
7.2%
i 67377
 
6.3%
l 57837
 
5.4%
s 49634
 
4.6%
t 34423
 
3.2%
d 28409
 
2.7%
Other values (42) 392042
36.6%
Common
ValueCountFrequency (%)
92840
94.4%
. 3140
 
3.2%
' 1279
 
1.3%
- 1129
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1168801
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 98914
 
8.5%
a 95597
 
8.2%
92840
 
7.9%
n 85538
 
7.3%
r 83604
 
7.2%
o 77038
 
6.6%
i 67377
 
5.8%
l 57837
 
4.9%
s 49634
 
4.2%
t 34423
 
2.9%
Other values (46) 425999
36.4%

player1_team_id
Text

MISSING 

Distinct50
Distinct (%)0.1%
Missing8976
Missing (%)9.0%
Memory size781.4 KiB
2023-07-13T22:06:12.208046image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.99537485
Min length4

Characters and Unicode

Total characters1091867
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1610612760.0
2nd row1610612742.0
3rd row1610612748.0
4th row1610612759.0
5th row1610612750.0
ValueCountFrequency (%)
1610612759.0 3232
 
3.6%
1610612747.0 3213
 
3.5%
1610612738.0 3210
 
3.5%
1610612748.0 3159
 
3.5%
1610612744.0 3153
 
3.5%
1610612743.0 3143
 
3.5%
1610612745.0 3139
 
3.4%
1610612755.0 3131
 
3.4%
1610612754.0 3122
 
3.4%
1610612749.0 3104
 
3.4%
Other values (40) 59418
65.3%
2023-07-13T22:06:12.458380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 281927
25.8%
6 211739
19.4%
0 190332
17.4%
7 100097
 
9.2%
2 100046
 
9.2%
. 91024
 
8.3%
5 39738
 
3.6%
4 39475
 
3.6%
3 18693
 
1.7%
8 9426
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1000843
91.7%
Other Punctuation 91024
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 281927
28.2%
6 211739
21.2%
0 190332
19.0%
7 100097
 
10.0%
2 100046
 
10.0%
5 39738
 
4.0%
4 39475
 
3.9%
3 18693
 
1.9%
8 9426
 
0.9%
9 9370
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 91024
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1091867
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 281927
25.8%
6 211739
19.4%
0 190332
17.4%
7 100097
 
9.2%
2 100046
 
9.2%
. 91024
 
8.3%
5 39738
 
3.6%
4 39475
 
3.6%
3 18693
 
1.7%
8 9426
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1091867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 281927
25.8%
6 211739
19.4%
0 190332
17.4%
7 100097
 
9.2%
2 100046
 
9.2%
. 91024
 
8.3%
5 39738
 
3.6%
4 39475
 
3.6%
3 18693
 
1.7%
8 9426
 
0.9%

player1_team_city
Text

MISSING 

Distinct55
Distinct (%)0.1%
Missing8976
Missing (%)9.0%
Memory size781.4 KiB
2023-07-13T22:06:12.623365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length13
Mean length8.251801723
Min length2

Characters and Unicode

Total characters751112
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowSeattle
2nd rowDallas
3rd rowMiami
4th rowSan Antonio
5th rowMinnesota
ValueCountFrequency (%)
new 7140
 
6.4%
angeles 5184
 
4.6%
los 5184
 
4.6%
antonio 3232
 
2.9%
san 3232
 
2.9%
boston 3210
 
2.9%
miami 3159
 
2.8%
golden 3153
 
2.8%
state 3153
 
2.8%
denver 3143
 
2.8%
Other values (55) 72228
64.5%
2023-07-13T22:06:12.844361image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 75218
 
10.0%
e 71577
 
9.5%
o 71349
 
9.5%
n 70817
 
9.4%
t 56204
 
7.5%
l 48544
 
6.5%
i 41535
 
5.5%
s 32381
 
4.3%
r 29839
 
4.0%
h 25571
 
3.4%
Other values (39) 228077
30.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 616543
82.1%
Uppercase Letter 113373
 
15.1%
Space Separator 20994
 
2.8%
Other Punctuation 202
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 75218
12.2%
e 71577
11.6%
o 71349
11.6%
n 70817
11.5%
t 56204
9.1%
l 48544
7.9%
i 41535
6.7%
s 32381
 
5.3%
r 29839
 
4.8%
h 25571
 
4.1%
Other values (14) 93508
15.2%
Uppercase Letter
ValueCountFrequency (%)
A 12684
11.2%
M 11676
10.3%
C 10686
9.4%
S 10665
9.4%
D 9186
 
8.1%
P 9126
 
8.0%
O 7355
 
6.5%
N 7220
 
6.4%
L 6184
 
5.5%
B 4563
 
4.0%
Other values (12) 24028
21.2%
Other Punctuation
ValueCountFrequency (%)
/ 195
96.5%
' 7
 
3.5%
Space Separator
ValueCountFrequency (%)
20994
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 729916
97.2%
Common 21196
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 75218
 
10.3%
e 71577
 
9.8%
o 71349
 
9.8%
n 70817
 
9.7%
t 56204
 
7.7%
l 48544
 
6.7%
i 41535
 
5.7%
s 32381
 
4.4%
r 29839
 
4.1%
h 25571
 
3.5%
Other values (36) 206881
28.3%
Common
ValueCountFrequency (%)
20994
99.0%
/ 195
 
0.9%
' 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 751112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 75218
 
10.0%
e 71577
 
9.5%
o 71349
 
9.5%
n 70817
 
9.4%
t 56204
 
7.5%
l 48544
 
6.5%
i 41535
 
5.5%
s 32381
 
4.3%
r 29839
 
4.0%
h 25571
 
3.4%
Other values (39) 228077
30.4%

player1_team_nickname
Text

MISSING 

Distinct58
Distinct (%)0.1%
Missing8976
Missing (%)9.0%
Memory size781.4 KiB
2023-07-13T22:06:13.009357image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length22
Median length18
Mean length6.70881306
Min length4

Characters and Unicode

Total characters610663
Distinct characters49
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowSuperSonics
2nd rowMavericks
3rd rowHeat
4th rowSpurs
5th rowTimberwolves
ValueCountFrequency (%)
spurs 3232
 
3.4%
lakers 3213
 
3.4%
celtics 3210
 
3.4%
heat 3159
 
3.4%
warriors 3153
 
3.4%
nuggets 3143
 
3.3%
rockets 3139
 
3.3%
76ers 3131
 
3.3%
pacers 3122
 
3.3%
bucks 3104
 
3.3%
Other values (58) 62401
66.4%
2023-07-13T22:06:13.235412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 82918
 
13.6%
r 54789
 
9.0%
e 53278
 
8.7%
a 45111
 
7.4%
i 44756
 
7.3%
l 28394
 
4.6%
t 25721
 
4.2%
c 25213
 
4.1%
o 20317
 
3.3%
n 19339
 
3.2%
Other values (39) 210827
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 509238
83.4%
Uppercase Letter 92167
 
15.1%
Decimal Number 6264
 
1.0%
Space Separator 2983
 
0.5%
Other Punctuation 9
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 82918
16.3%
r 54789
10.8%
e 53278
10.5%
a 45111
8.9%
i 44756
8.8%
l 28394
 
5.6%
t 25721
 
5.1%
c 25213
 
5.0%
o 20317
 
4.0%
n 19339
 
3.8%
Other values (12) 109402
21.5%
Uppercase Letter
ValueCountFrequency (%)
B 10075
10.9%
C 9199
10.0%
H 9045
9.8%
S 8821
9.6%
T 7682
8.3%
P 7449
8.1%
R 6208
6.7%
N 6166
6.7%
W 6081
 
6.6%
M 6036
 
6.5%
Other values (10) 15405
16.7%
Decimal Number
ValueCountFrequency (%)
6 3132
50.0%
7 3131
50.0%
3 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
' 7
77.8%
/ 2
 
22.2%
Space Separator
ValueCountFrequency (%)
2983
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 601405
98.5%
Common 9258
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 82918
13.8%
r 54789
 
9.1%
e 53278
 
8.9%
a 45111
 
7.5%
i 44756
 
7.4%
l 28394
 
4.7%
t 25721
 
4.3%
c 25213
 
4.2%
o 20317
 
3.4%
n 19339
 
3.2%
Other values (32) 201569
33.5%
Common
ValueCountFrequency (%)
6 3132
33.8%
7 3131
33.8%
2983
32.2%
' 7
 
0.1%
- 2
 
< 0.1%
/ 2
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 610663
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 82918
 
13.6%
r 54789
 
9.0%
e 53278
 
8.7%
a 45111
 
7.4%
i 44756
 
7.3%
l 28394
 
4.6%
t 25721
 
4.2%
c 25213
 
4.1%
o 20317
 
3.3%
n 19339
 
3.2%
Other values (39) 210827
34.5%
Distinct61
Distinct (%)0.1%
Missing8976
Missing (%)9.0%
Memory size781.4 KiB
2023-07-13T22:06:13.373531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters273072
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowSEA
2nd rowDAL
3rd rowMIA
4th rowSAS
5th rowMIN
ValueCountFrequency (%)
sas 3232
 
3.6%
lal 3213
 
3.5%
bos 3210
 
3.5%
mia 3159
 
3.5%
gsw 3153
 
3.5%
den 3143
 
3.5%
hou 3139
 
3.4%
phi 3131
 
3.4%
ind 3122
 
3.4%
mil 3104
 
3.4%
Other values (51) 59418
65.3%
2023-07-13T22:06:13.559191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 31610
11.6%
L 24649
 
9.0%
S 20131
 
7.4%
N 19876
 
7.3%
O 19506
 
7.1%
I 18343
 
6.7%
C 16419
 
6.0%
H 16412
 
6.0%
M 14195
 
5.2%
E 12980
 
4.8%
Other values (14) 78951
28.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 273072
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 31610
11.6%
L 24649
 
9.0%
S 20131
 
7.4%
N 19876
 
7.3%
O 19506
 
7.1%
I 18343
 
6.7%
C 16419
 
6.0%
H 16412
 
6.0%
M 14195
 
5.2%
E 12980
 
4.8%
Other values (14) 78951
28.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 273072
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 31610
11.6%
L 24649
 
9.0%
S 20131
 
7.4%
N 19876
 
7.3%
O 19506
 
7.1%
I 18343
 
6.7%
C 16419
 
6.0%
H 16412
 
6.0%
M 14195
 
5.2%
E 12980
 
4.8%
Other values (14) 78951
28.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 273072
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 31610
11.6%
L 24649
 
9.0%
S 20131
 
7.4%
N 19876
 
7.3%
O 19506
 
7.1%
I 18343
 
6.7%
C 16419
 
6.0%
H 16412
 
6.0%
M 14195
 
5.2%
E 12980
 
4.8%
Other values (14) 78951
28.9%

person2type
Real number (ℝ)

ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.29786
Minimum0
Maximum5
Zeros71170
Zeros (%)71.2%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:13.615246image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.056798902
Coefficient of variation (CV)1.584761763
Kurtosis-0.9405920634
Mean1.29786
Median Absolute Deviation (MAD)0
Skewness0.9905831805
Sum129786
Variance4.230421725
MonotonicityNot monotonic
2023-07-13T22:06:13.659305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 71170
71.2%
5 14470
 
14.5%
4 14356
 
14.4%
3 4
 
< 0.1%
ValueCountFrequency (%)
0 71170
71.2%
3 4
 
< 0.1%
4 14356
 
14.4%
5 14470
 
14.5%
ValueCountFrequency (%)
5 14470
 
14.5%
4 14356
 
14.4%
3 4
 
< 0.1%
0 71170
71.2%
Distinct1934
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:13.900931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length1
Mean length2.1615
Min length1

Characters and Unicode

Total characters216150
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique350 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row200761
5th row0
ValueCountFrequency (%)
0 71348
71.3%
2544 178
 
0.2%
201566 150
 
0.1%
101108 146
 
0.1%
201935 126
 
0.1%
467 113
 
0.1%
2225 112
 
0.1%
977 111
 
0.1%
1938 108
 
0.1%
2548 107
 
0.1%
Other values (1924) 27501
 
27.5%
2023-07-13T22:06:14.217601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 92031
42.6%
2 27672
 
12.8%
1 23552
 
10.9%
6 12738
 
5.9%
3 11536
 
5.3%
9 10928
 
5.1%
7 10707
 
5.0%
5 9408
 
4.4%
4 9136
 
4.2%
8 8442
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 216150
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 92031
42.6%
2 27672
 
12.8%
1 23552
 
10.9%
6 12738
 
5.9%
3 11536
 
5.3%
9 10928
 
5.1%
7 10707
 
5.0%
5 9408
 
4.4%
4 9136
 
4.2%
8 8442
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
Common 216150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 92031
42.6%
2 27672
 
12.8%
1 23552
 
10.9%
6 12738
 
5.9%
3 11536
 
5.3%
9 10928
 
5.1%
7 10707
 
5.0%
5 9408
 
4.4%
4 9136
 
4.2%
8 8442
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 216150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 92031
42.6%
2 27672
 
12.8%
1 23552
 
10.9%
6 12738
 
5.9%
3 11536
 
5.3%
9 10928
 
5.1%
7 10707
 
5.0%
5 9408
 
4.4%
4 9136
 
4.2%
8 8442
 
3.9%

player2_name
Text

MISSING 

Distinct1917
Distinct (%)6.7%
Missing71359
Missing (%)71.4%
Memory size781.4 KiB
2023-07-13T22:06:14.517370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.75336057
Min length4

Characters and Unicode

Total characters365269
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique339 ?
Unique (%)1.2%

Sample

1st rowShawne Williams
2nd rowMarco Belinelli
3rd rowFred Hoiberg
4th rowTerry Rozier
5th rowSteven Smith
ValueCountFrequency (%)
williams 594
 
1.0%
chris 500
 
0.9%
james 450
 
0.8%
paul 405
 
0.7%
jason 403
 
0.7%
anthony 370
 
0.6%
kevin 368
 
0.6%
johnson 338
 
0.6%
mike 321
 
0.6%
davis 302
 
0.5%
Other values (2212) 53751
93.0%
2023-07-13T22:06:14.876439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 30794
 
8.4%
a 29450
 
8.1%
29161
 
8.0%
n 26836
 
7.3%
r 26420
 
7.2%
o 24370
 
6.7%
i 20824
 
5.7%
l 18072
 
4.9%
s 15544
 
4.3%
t 10607
 
2.9%
Other values (46) 133191
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 273626
74.9%
Uppercase Letter 60623
 
16.6%
Space Separator 29161
 
8.0%
Other Punctuation 1516
 
0.4%
Dash Punctuation 343
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 30794
11.3%
a 29450
10.8%
n 26836
9.8%
r 26420
9.7%
o 24370
 
8.9%
i 20824
 
7.6%
l 18072
 
6.6%
s 15544
 
5.7%
t 10607
 
3.9%
d 8725
 
3.2%
Other values (16) 61984
22.7%
Uppercase Letter
ValueCountFrequency (%)
J 6416
 
10.6%
M 5364
 
8.8%
D 4880
 
8.0%
B 4601
 
7.6%
C 3852
 
6.4%
A 3705
 
6.1%
S 3539
 
5.8%
R 3445
 
5.7%
T 3031
 
5.0%
G 2795
 
4.6%
Other values (16) 18995
31.3%
Other Punctuation
ValueCountFrequency (%)
. 1149
75.8%
' 367
 
24.2%
Space Separator
ValueCountFrequency (%)
29161
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 343
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 334249
91.5%
Common 31020
 
8.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 30794
 
9.2%
a 29450
 
8.8%
n 26836
 
8.0%
r 26420
 
7.9%
o 24370
 
7.3%
i 20824
 
6.2%
l 18072
 
5.4%
s 15544
 
4.7%
t 10607
 
3.2%
d 8725
 
2.6%
Other values (42) 122607
36.7%
Common
ValueCountFrequency (%)
29161
94.0%
. 1149
 
3.7%
' 367
 
1.2%
- 343
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 365269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 30794
 
8.4%
a 29450
 
8.1%
29161
 
8.0%
n 26836
 
7.3%
r 26420
 
7.2%
o 24370
 
6.7%
i 20824
 
5.7%
l 18072
 
4.9%
s 15544
 
4.3%
t 10607
 
2.9%
Other values (46) 133191
36.5%

player2_team_id
Text

MISSING 

Distinct43
Distinct (%)0.1%
Missing71174
Missing (%)71.2%
Memory size781.4 KiB
2023-07-13T22:06:15.074231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.99441476
Min length4

Characters and Unicode

Total characters345751
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1610612754.0
2nd row1610612759.0
3rd row1610612750.0
4th row1610612766.0
5th row1610612737.0
ValueCountFrequency (%)
1610612759.0 1112
 
3.9%
1610612763.0 1037
 
3.6%
1610612756.0 1036
 
3.6%
1610612738.0 1029
 
3.6%
1610612747.0 1026
 
3.6%
1610612762.0 1026
 
3.6%
1610612754.0 1015
 
3.5%
1610612743.0 1012
 
3.5%
1610612755.0 996
 
3.5%
1610612760.0 985
 
3.4%
Other values (33) 18552
64.4%
2023-07-13T22:06:15.325314image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 89207
25.8%
6 67041
19.4%
0 60257
17.4%
7 31738
 
9.2%
2 31708
 
9.2%
. 28826
 
8.3%
5 12620
 
3.7%
4 12343
 
3.6%
3 6053
 
1.8%
9 3018
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 316925
91.7%
Other Punctuation 28826
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 89207
28.1%
6 67041
21.2%
0 60257
19.0%
7 31738
 
10.0%
2 31708
 
10.0%
5 12620
 
4.0%
4 12343
 
3.9%
3 6053
 
1.9%
9 3018
 
1.0%
8 2940
 
0.9%
Other Punctuation
ValueCountFrequency (%)
. 28826
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 345751
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 89207
25.8%
6 67041
19.4%
0 60257
17.4%
7 31738
 
9.2%
2 31708
 
9.2%
. 28826
 
8.3%
5 12620
 
3.7%
4 12343
 
3.6%
3 6053
 
1.8%
9 3018
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 345751
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 89207
25.8%
6 67041
19.4%
0 60257
17.4%
7 31738
 
9.2%
2 31708
 
9.2%
. 28826
 
8.3%
5 12620
 
3.7%
4 12343
 
3.6%
3 6053
 
1.8%
9 3018
 
0.9%

player2_team_city
Text

MISSING 

Distinct48
Distinct (%)0.2%
Missing71174
Missing (%)71.2%
Memory size781.4 KiB
2023-07-13T22:06:15.485683image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length13
Mean length8.229376258
Min length2

Characters and Unicode

Total characters237220
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowIndiana
2nd rowSan Antonio
3rd rowMinnesota
4th rowCharlotte
5th rowAtlanta
ValueCountFrequency (%)
new 2212
 
6.2%
los 1596
 
4.5%
angeles 1596
 
4.5%
san 1112
 
3.1%
antonio 1112
 
3.1%
phoenix 1036
 
2.9%
boston 1029
 
2.9%
utah 1026
 
2.9%
indiana 1015
 
2.9%
denver 1012
 
2.9%
Other values (47) 22757
64.1%
2023-07-13T22:06:15.695481image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 23790
 
10.0%
n 22628
 
9.5%
o 22459
 
9.5%
e 22311
 
9.4%
t 17533
 
7.4%
l 15368
 
6.5%
i 13181
 
5.6%
s 10170
 
4.3%
r 9288
 
3.9%
h 8222
 
3.5%
Other values (39) 72270
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 194466
82.0%
Uppercase Letter 36014
 
15.2%
Space Separator 6677
 
2.8%
Other Punctuation 63
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 23790
12.2%
n 22628
11.6%
o 22459
11.5%
e 22311
11.5%
t 17533
9.0%
l 15368
7.9%
i 13181
6.8%
s 10170
 
5.2%
r 9288
 
4.8%
h 8222
 
4.2%
Other values (14) 29516
15.2%
Uppercase Letter
ValueCountFrequency (%)
A 4143
11.5%
M 3688
10.2%
S 3383
9.4%
C 3344
9.3%
P 3002
8.3%
D 2859
 
7.9%
O 2361
 
6.6%
N 2242
 
6.2%
L 1987
 
5.5%
B 1503
 
4.2%
Other values (12) 7502
20.8%
Other Punctuation
ValueCountFrequency (%)
/ 60
95.2%
' 3
 
4.8%
Space Separator
ValueCountFrequency (%)
6677
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 230480
97.2%
Common 6740
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 23790
 
10.3%
n 22628
 
9.8%
o 22459
 
9.7%
e 22311
 
9.7%
t 17533
 
7.6%
l 15368
 
6.7%
i 13181
 
5.7%
s 10170
 
4.4%
r 9288
 
4.0%
h 8222
 
3.6%
Other values (36) 65530
28.4%
Common
ValueCountFrequency (%)
6677
99.1%
/ 60
 
0.9%
' 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 237220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 23790
 
10.0%
n 22628
 
9.5%
o 22459
 
9.5%
e 22311
 
9.4%
t 17533
 
7.4%
l 15368
 
6.5%
i 13181
 
5.6%
s 10170
 
4.3%
r 9288
 
3.9%
h 8222
 
3.5%
Other values (39) 72270
30.5%

player2_team_nickname
Text

MISSING 

Distinct48
Distinct (%)0.2%
Missing71174
Missing (%)71.2%
Memory size781.4 KiB
2023-07-13T22:06:15.856053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length22
Median length16
Mean length6.711163533
Min length4

Characters and Unicode

Total characters193456
Distinct characters45
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowPacers
2nd rowSpurs
3rd rowTimberwolves
4th rowHornets
5th rowHawks
ValueCountFrequency (%)
spurs 1112
 
3.7%
grizzlies 1037
 
3.5%
suns 1036
 
3.5%
celtics 1029
 
3.5%
lakers 1026
 
3.4%
jazz 1026
 
3.4%
pacers 1015
 
3.4%
nuggets 1012
 
3.4%
76ers 996
 
3.3%
warriors 983
 
3.3%
Other values (44) 19544
65.5%
2023-07-13T22:06:16.079757image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 26126
 
13.5%
r 17476
 
9.0%
e 16992
 
8.8%
a 14442
 
7.5%
i 14193
 
7.3%
l 9123
 
4.7%
t 7981
 
4.1%
c 7900
 
4.1%
o 6161
 
3.2%
n 6012
 
3.1%
Other values (35) 67050
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 161280
83.4%
Uppercase Letter 29189
 
15.1%
Decimal Number 1992
 
1.0%
Space Separator 990
 
0.5%
Other Punctuation 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 26126
16.2%
r 17476
10.8%
e 16992
10.5%
a 14442
9.0%
i 14193
8.8%
l 9123
 
5.7%
t 7981
 
4.9%
c 7900
 
4.9%
o 6161
 
3.8%
n 6012
 
3.7%
Other values (12) 34874
21.6%
Uppercase Letter
ValueCountFrequency (%)
B 3123
10.7%
C 2968
10.2%
S 2880
9.9%
H 2772
9.5%
T 2483
8.5%
P 2345
8.0%
N 1986
6.8%
M 1909
 
6.5%
R 1907
 
6.5%
W 1859
 
6.4%
Other values (7) 4957
17.0%
Decimal Number
ValueCountFrequency (%)
6 996
50.0%
7 996
50.0%
Other Punctuation
ValueCountFrequency (%)
' 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
990
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 190469
98.5%
Common 2987
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 26126
13.7%
r 17476
 
9.2%
e 16992
 
8.9%
a 14442
 
7.6%
i 14193
 
7.5%
l 9123
 
4.8%
t 7981
 
4.2%
c 7900
 
4.1%
o 6161
 
3.2%
n 6012
 
3.2%
Other values (29) 64063
33.6%
Common
ValueCountFrequency (%)
6 996
33.3%
7 996
33.3%
990
33.1%
' 3
 
0.1%
/ 1
 
< 0.1%
- 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 193456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 26126
 
13.5%
r 17476
 
9.0%
e 16992
 
8.8%
a 14442
 
7.5%
i 14193
 
7.3%
l 9123
 
4.7%
t 7981
 
4.1%
c 7900
 
4.1%
o 6161
 
3.2%
n 6012
 
3.1%
Other values (35) 67050
34.7%
Distinct52
Distinct (%)0.2%
Missing71174
Missing (%)71.2%
Memory size781.4 KiB
2023-07-13T22:06:16.221614image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters86478
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowIND
2nd rowSAS
3rd rowMIN
4th rowCHA
5th rowATL
ValueCountFrequency (%)
sas 1112
 
3.9%
phx 1036
 
3.6%
bos 1029
 
3.6%
uta 1026
 
3.6%
lal 1026
 
3.6%
ind 1015
 
3.5%
den 1012
 
3.5%
phi 996
 
3.5%
gsw 983
 
3.4%
atl 981
 
3.4%
Other values (42) 18610
64.6%
2023-07-13T22:06:16.410603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 10045
 
11.6%
L 7796
 
9.0%
S 6437
 
7.4%
N 6261
 
7.2%
O 6199
 
7.2%
I 5677
 
6.6%
C 5141
 
5.9%
H 5071
 
5.9%
M 4587
 
5.3%
E 4151
 
4.8%
Other values (14) 25113
29.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 86478
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 10045
 
11.6%
L 7796
 
9.0%
S 6437
 
7.4%
N 6261
 
7.2%
O 6199
 
7.2%
I 5677
 
6.6%
C 5141
 
5.9%
H 5071
 
5.9%
M 4587
 
5.3%
E 4151
 
4.8%
Other values (14) 25113
29.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 86478
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 10045
 
11.6%
L 7796
 
9.0%
S 6437
 
7.4%
N 6261
 
7.2%
O 6199
 
7.2%
I 5677
 
6.6%
C 5141
 
5.9%
H 5071
 
5.9%
M 4587
 
5.3%
E 4151
 
4.8%
Other values (14) 25113
29.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86478
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 10045
 
11.6%
L 7796
 
9.0%
S 6437
 
7.4%
N 6261
 
7.2%
O 6199
 
7.2%
I 5677
 
6.6%
C 5141
 
5.9%
H 5071
 
5.9%
M 4587
 
5.3%
E 4151
 
4.8%
Other values (14) 25113
29.0%

person3type
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22606
Minimum0
Maximum5
Zeros86194
Zeros (%)86.2%
Negative0
Negative (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:16.467334image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7566258
Coefficient of variation (CV)3.347013182
Kurtosis23.9679247
Mean0.22606
Median Absolute Deviation (MAD)0
Skewness4.715508387
Sum22606
Variance0.5724826012
MonotonicityNot monotonic
2023-07-13T22:06:16.510005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 86194
86.2%
1 11246
 
11.2%
4 1389
 
1.4%
5 1149
 
1.1%
3 15
 
< 0.1%
2 7
 
< 0.1%
ValueCountFrequency (%)
0 86194
86.2%
1 11246
 
11.2%
2 7
 
< 0.1%
3 15
 
< 0.1%
4 1389
 
1.4%
ValueCountFrequency (%)
5 1149
 
1.1%
4 1389
 
1.4%
3 15
 
< 0.1%
2 7
 
< 0.1%
1 11246
11.2%
Distinct937
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:16.750095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length10
Median length1
Mean length1.09743
Min length1

Characters and Unicode

Total characters109743
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique419 ?
Unique (%)0.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 97480
97.5%
1495 26
 
< 0.1%
689 19
 
< 0.1%
2746 18
 
< 0.1%
948 18
 
< 0.1%
708 18
 
< 0.1%
2544 17
 
< 0.1%
87 17
 
< 0.1%
2730 16
 
< 0.1%
406 16
 
< 0.1%
Other values (927) 2355
 
2.4%
2023-07-13T22:06:17.055591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 99170
90.4%
2 2323
 
2.1%
1 1924
 
1.8%
6 1110
 
1.0%
9 988
 
0.9%
3 972
 
0.9%
7 914
 
0.8%
4 806
 
0.7%
5 785
 
0.7%
8 751
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 109743
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 99170
90.4%
2 2323
 
2.1%
1 1924
 
1.8%
6 1110
 
1.0%
9 988
 
0.9%
3 972
 
0.9%
7 914
 
0.8%
4 806
 
0.7%
5 785
 
0.7%
8 751
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Common 109743
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 99170
90.4%
2 2323
 
2.1%
1 1924
 
1.8%
6 1110
 
1.0%
9 988
 
0.9%
3 972
 
0.9%
7 914
 
0.8%
4 806
 
0.7%
5 785
 
0.7%
8 751
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109743
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 99170
90.4%
2 2323
 
2.1%
1 1924
 
1.8%
6 1110
 
1.0%
9 988
 
0.9%
3 972
 
0.9%
7 914
 
0.8%
4 806
 
0.7%
5 785
 
0.7%
8 751
 
0.7%

player3_name
Text

MISSING 

Distinct917
Distinct (%)36.7%
Missing97504
Missing (%)97.5%
Memory size781.4 KiB
2023-07-13T22:06:17.373857image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length24
Median length22
Mean length12.92788462
Min length4

Characters and Unicode

Total characters32268
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique404 ?
Unique (%)16.2%

Sample

1st rowSerge Ibaka
2nd rowTroy Hudson
3rd rowSebastian Telfair
4th rowDeMarcus Cousins
5th rowCalvin Booth
ValueCountFrequency (%)
williams 55
 
1.1%
chris 49
 
1.0%
james 39
 
0.8%
kevin 39
 
0.8%
smith 32
 
0.6%
anthony 30
 
0.6%
josh 30
 
0.6%
tim 29
 
0.6%
davis 28
 
0.6%
duncan 27
 
0.5%
Other values (1234) 4680
92.9%
2023-07-13T22:06:17.752985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2699
 
8.4%
a 2657
 
8.2%
2542
 
7.9%
n 2333
 
7.2%
r 2217
 
6.9%
o 2105
 
6.5%
i 1923
 
6.0%
l 1621
 
5.0%
s 1296
 
4.0%
t 1071
 
3.3%
Other values (46) 11804
36.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24269
75.2%
Uppercase Letter 5320
 
16.5%
Space Separator 2542
 
7.9%
Other Punctuation 105
 
0.3%
Dash Punctuation 32
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2699
11.1%
a 2657
10.9%
n 2333
9.6%
r 2217
 
9.1%
o 2105
 
8.7%
i 1923
 
7.9%
l 1621
 
6.7%
s 1296
 
5.3%
t 1071
 
4.4%
d 758
 
3.1%
Other values (16) 5589
23.0%
Uppercase Letter
ValueCountFrequency (%)
J 478
 
9.0%
M 477
 
9.0%
D 439
 
8.3%
B 367
 
6.9%
A 349
 
6.6%
C 335
 
6.3%
T 295
 
5.5%
S 295
 
5.5%
G 283
 
5.3%
R 273
 
5.1%
Other values (16) 1729
32.5%
Other Punctuation
ValueCountFrequency (%)
. 58
55.2%
' 47
44.8%
Space Separator
ValueCountFrequency (%)
2542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 29589
91.7%
Common 2679
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2699
 
9.1%
a 2657
 
9.0%
n 2333
 
7.9%
r 2217
 
7.5%
o 2105
 
7.1%
i 1923
 
6.5%
l 1621
 
5.5%
s 1296
 
4.4%
t 1071
 
3.6%
d 758
 
2.6%
Other values (42) 10909
36.9%
Common
ValueCountFrequency (%)
2542
94.9%
. 58
 
2.2%
' 47
 
1.8%
- 32
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32268
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 2699
 
8.4%
a 2657
 
8.2%
2542
 
7.9%
n 2333
 
7.2%
r 2217
 
6.9%
o 2105
 
6.5%
i 1923
 
6.0%
l 1621
 
5.0%
s 1296
 
4.0%
t 1071
 
3.3%
Other values (46) 11804
36.6%

player3_team_id
Text

MISSING 

Distinct34
Distinct (%)1.3%
Missing97462
Missing (%)97.5%
Memory size781.4 KiB
2023-07-13T22:06:17.964317image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.99605989
Min length7

Characters and Unicode

Total characters30446
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row1610612760.0
2nd row1610612750.0
3rd row1610612738.0
4th row1610612758.0
5th row1610612764.0
ValueCountFrequency (%)
1610612759.0 107
 
4.2%
1610612754.0 102
 
4.0%
1610612743.0 101
 
4.0%
1610612747.0 101
 
4.0%
1610612755.0 99
 
3.9%
1610612737.0 98
 
3.9%
1610612761.0 97
 
3.8%
1610612750.0 92
 
3.6%
1610612742.0 92
 
3.6%
1610612756.0 92
 
3.6%
Other values (24) 1557
61.3%
2023-07-13T22:06:18.201113image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 7870
25.8%
6 5894
19.4%
0 5298
17.4%
7 2808
 
9.2%
2 2791
 
9.2%
. 2538
 
8.3%
5 1133
 
3.7%
4 1103
 
3.6%
3 524
 
1.7%
9 259
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 27908
91.7%
Other Punctuation 2538
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7870
28.2%
6 5894
21.1%
0 5298
19.0%
7 2808
 
10.1%
2 2791
 
10.0%
5 1133
 
4.1%
4 1103
 
4.0%
3 524
 
1.9%
9 259
 
0.9%
8 228
 
0.8%
Other Punctuation
ValueCountFrequency (%)
. 2538
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 7870
25.8%
6 5894
19.4%
0 5298
17.4%
7 2808
 
9.2%
2 2791
 
9.2%
. 2538
 
8.3%
5 1133
 
3.7%
4 1103
 
3.6%
3 524
 
1.7%
9 259
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 7870
25.8%
6 5894
19.4%
0 5298
17.4%
7 2808
 
9.2%
2 2791
 
9.2%
. 2538
 
8.3%
5 1133
 
3.7%
4 1103
 
3.6%
3 524
 
1.7%
9 259
 
0.9%

player3_team_city
Text

MISSING 

Distinct39
Distinct (%)1.5%
Missing97462
Missing (%)97.5%
Memory size781.4 KiB
2023-07-13T22:06:18.354346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length25
Median length13
Mean length8.267533491
Min length2

Characters and Unicode

Total characters20983
Distinct characters44
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st rowOklahoma City
2nd rowMinnesota
3rd rowBoston
4th rowSacramento
5th rowWashington
ValueCountFrequency (%)
new 184
 
5.9%
los 146
 
4.7%
angeles 146
 
4.7%
antonio 107
 
3.4%
san 107
 
3.4%
indiana 102
 
3.3%
denver 101
 
3.2%
philadelphia 99
 
3.2%
atlanta 98
 
3.1%
toronto 97
 
3.1%
Other values (37) 1934
62.0%
2023-07-13T22:06:18.560305image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 2146
 
10.2%
n 2078
 
9.9%
o 1997
 
9.5%
e 1944
 
9.3%
t 1551
 
7.4%
l 1351
 
6.4%
i 1183
 
5.6%
s 897
 
4.3%
r 813
 
3.9%
h 745
 
3.6%
Other values (34) 6278
29.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 17239
82.2%
Uppercase Letter 3157
 
15.0%
Space Separator 583
 
2.8%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2146
12.4%
n 2078
12.1%
o 1997
11.6%
e 1944
11.3%
t 1551
9.0%
l 1351
7.8%
i 1183
6.9%
s 897
 
5.2%
r 813
 
4.7%
h 745
 
4.3%
Other values (12) 2534
14.7%
Uppercase Letter
ValueCountFrequency (%)
A 383
12.1%
M 308
9.8%
C 295
9.3%
S 292
9.2%
P 267
 
8.5%
D 266
 
8.4%
O 195
 
6.2%
N 186
 
5.9%
L 174
 
5.5%
B 108
 
3.4%
Other values (10) 683
21.6%
Space Separator
ValueCountFrequency (%)
583
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20396
97.2%
Common 587
 
2.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2146
 
10.5%
n 2078
 
10.2%
o 1997
 
9.8%
e 1944
 
9.5%
t 1551
 
7.6%
l 1351
 
6.6%
i 1183
 
5.8%
s 897
 
4.4%
r 813
 
4.0%
h 745
 
3.7%
Other values (32) 5691
27.9%
Common
ValueCountFrequency (%)
583
99.3%
/ 4
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2146
 
10.2%
n 2078
 
9.9%
o 1997
 
9.5%
e 1944
 
9.3%
t 1551
 
7.4%
l 1351
 
6.4%
i 1183
 
5.6%
s 897
 
4.3%
r 813
 
3.9%
h 745
 
3.6%
Other values (34) 6278
29.9%

player3_team_nickname
Text

MISSING 

Distinct38
Distinct (%)1.5%
Missing97462
Missing (%)97.5%
Memory size781.4 KiB
2023-07-13T22:06:18.724229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length22
Median length13
Mean length6.692671395
Min length4

Characters and Unicode

Total characters16986
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st rowThunder
2nd rowTimberwolves
3rd rowCeltics
4th rowKings
5th rowWizards
ValueCountFrequency (%)
spurs 107
 
4.1%
pacers 102
 
3.9%
nuggets 101
 
3.9%
lakers 101
 
3.9%
76ers 99
 
3.8%
hawks 98
 
3.7%
raptors 97
 
3.7%
timberwolves 92
 
3.5%
mavericks 92
 
3.5%
suns 92
 
3.5%
Other values (32) 1636
62.5%
2023-07-13T22:06:18.937941image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 2316
 
13.6%
r 1566
 
9.2%
e 1489
 
8.8%
a 1282
 
7.5%
i 1189
 
7.0%
l 769
 
4.5%
t 688
 
4.1%
c 675
 
4.0%
o 554
 
3.3%
u 537
 
3.2%
Other values (30) 5921
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14166
83.4%
Uppercase Letter 2543
 
15.0%
Decimal Number 198
 
1.2%
Space Separator 79
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 2316
16.3%
r 1566
11.1%
e 1489
10.5%
a 1282
9.0%
i 1189
 
8.4%
l 769
 
5.4%
t 688
 
4.9%
c 675
 
4.8%
o 554
 
3.9%
u 537
 
3.8%
Other values (11) 3101
21.9%
Uppercase Letter
ValueCountFrequency (%)
B 268
10.5%
S 248
9.8%
H 245
9.6%
C 229
9.0%
T 218
8.6%
P 211
8.3%
R 178
7.0%
N 178
7.0%
M 176
6.9%
W 171
6.7%
Other values (6) 421
16.6%
Decimal Number
ValueCountFrequency (%)
7 99
50.0%
6 99
50.0%
Space Separator
ValueCountFrequency (%)
79
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16709
98.4%
Common 277
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 2316
13.9%
r 1566
 
9.4%
e 1489
 
8.9%
a 1282
 
7.7%
i 1189
 
7.1%
l 769
 
4.6%
t 688
 
4.1%
c 675
 
4.0%
o 554
 
3.3%
u 537
 
3.2%
Other values (27) 5644
33.8%
Common
ValueCountFrequency (%)
7 99
35.7%
6 99
35.7%
79
28.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16986
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 2316
 
13.6%
r 1566
 
9.2%
e 1489
 
8.8%
a 1282
 
7.5%
i 1189
 
7.0%
l 769
 
4.5%
t 688
 
4.1%
c 675
 
4.0%
o 554
 
3.3%
u 537
 
3.2%
Other values (30) 5921
34.9%
Distinct41
Distinct (%)1.6%
Missing97462
Missing (%)97.5%
Memory size781.4 KiB
2023-07-13T22:06:19.081980image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters7614
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st rowOKC
2nd rowMIN
3rd rowBOS
4th rowSAC
5th rowWAS
ValueCountFrequency (%)
sas 107
 
4.2%
ind 102
 
4.0%
den 101
 
4.0%
lal 101
 
4.0%
phi 99
 
3.9%
atl 98
 
3.9%
tor 97
 
3.8%
phx 92
 
3.6%
min 92
 
3.6%
dal 92
 
3.6%
Other values (31) 1557
61.3%
2023-07-13T22:06:19.273045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 889
11.7%
L 701
 
9.2%
N 573
 
7.5%
S 564
 
7.4%
I 526
 
6.9%
O 520
 
6.8%
H 472
 
6.2%
C 437
 
5.7%
M 374
 
4.9%
D 369
 
4.8%
Other values (14) 2189
28.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 7614
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 889
11.7%
L 701
 
9.2%
N 573
 
7.5%
S 564
 
7.4%
I 526
 
6.9%
O 520
 
6.8%
H 472
 
6.2%
C 437
 
5.7%
M 374
 
4.9%
D 369
 
4.8%
Other values (14) 2189
28.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 7614
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 889
11.7%
L 701
 
9.2%
N 573
 
7.5%
S 564
 
7.4%
I 526
 
6.9%
O 520
 
6.8%
H 472
 
6.2%
C 437
 
5.7%
M 374
 
4.9%
D 369
 
4.8%
Other values (14) 2189
28.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7614
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 889
11.7%
L 701
 
9.2%
N 573
 
7.5%
S 564
 
7.4%
I 526
 
6.9%
O 520
 
6.8%
H 472
 
6.2%
C 437
 
5.7%
M 374
 
4.9%
D 369
 
4.8%
Other values (14) 2189
28.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size781.4 KiB
2023-07-13T22:06:19.324073image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters100000
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 72285
72.3%
1 27715
 
27.7%
2023-07-13T22:06:19.416137image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 72285
72.3%
1 27715
 
27.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100000
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72285
72.3%
1 27715
 
27.7%

Most occurring scripts

ValueCountFrequency (%)
Common 100000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 72285
72.3%
1 27715
 
27.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 100000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 72285
72.3%
1 27715
 
27.7%